Neural Network Approach for Optimizing the Bioscouring Performance of Organic Cotton Fabric through Aerodynamic System

C. Vigneswaran, M. Ananthasubramanian, N. Anbumani

Abstract

The process optimization of bioscouring of 100% organic cotton fabric through enzyme technology with aerodynamic system have been studied with selective specific mixed enzymatic system using four enzymes namely alkaline pectinase, protease, lipase and cellulase. The process variables such as enzyme concentration, temperature and reaction time are optimized to achieve the required water absorbency and pectin removal during bioscouring process by pectinolytic and proteolytic activity on the organic cotton fabrics. These process variables are selected based on the artificial neural network (ANN) and output of experiment was resulted with fabric physic properties such as fabric weight loss, water absorbency, wetting area, whiteness index, yellowness index, and brightness index using MATLAB 7.0 software with minimum error and also studied with and without aerodynamic treatments. The test results are analyzed to predict the optimum process parameters to achieve the required bioscouring fabric properties and removal of pectin degrading rate and compared their results with actual trials. This study will be helpful to the organic cotton processors for the eco-friendly and sustainable textile wet processing using specific mixed enzymatic system in bioscouring processes.